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Entry Level Material Science Engineering Jobs in Massachusetts

Process Engineer IV

Gloucester, MA · On-site

$128K - $176K/yr

If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. What We Offer Salary: $128 ...

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage ...

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Entry Level Material Science Engineering information

See Massachusetts salary details

$14

$29

$48

How much do entry level material science engineering jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for entry level material science engineering in Massachusetts is $29.18, according to ZipRecruiter salary data. Most workers in this role earn between $21.25 and $35.96 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Material Science Engineering vs Entry Level Metallurgical Engineering?

AspectEntry Level Material Science EngineeringEntry Level Metallurgical Engineering
Required CredentialsBachelor's in Materials Science, Engineering, or related fieldBachelor's in Metallurgical Engineering or Materials Science
Work EnvironmentResearch labs, manufacturing plants, R&D departmentsMining sites, metal production facilities, manufacturing plants
Industry UsageAutomotive, aerospace, electronics, consumer productsMining, metal extraction, alloy development, manufacturing

Entry Level Material Science Engineering and Entry Level Metallurgical Engineering share foundational knowledge and often overlap in industries like manufacturing and R&D. However, Material Science focuses more on the properties and applications of materials, while Metallurgical Engineering emphasizes metal extraction and processing. Both roles typically require a bachelor's degree and involve work in labs or industrial settings, but their specific industry applications differ slightly.

What are popular job titles related to Entry Level Material Science Engineering jobs in Massachusetts?

For Entry Level Material Science Engineering jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Entry Level Material Science Engineering jobs in Massachusetts look for?

The top searched job categories for Entry Level Material Science Engineering jobs in Massachusetts are:

Infographic showing various Entry Level Material Science Engineering job openings in Massachusetts as of July 2026, with employment types broken down into 89% Full Time, 7% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $60,686 per year, or $29.2 per hour.

AI Residency Program, Material Science (2026 Cohort)

Lila Sciences

Cambridge, MA • On-site, Remote

Full-time

Re-posted 21 days ago


Job description

AI Resident - 2026 Cohort

The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science. Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research.

  • Duration: 6-12 months (extension possible)
  • Start Dates: First hires beginning January 2026, with rolling applications and additional intakes in Summer and Fall 2026
  • Cohort Size: Small group of selected residents
  • Mentorship: Pairing with technical mentors, feedback from cross-functional teams
  • Resources: Access to proprietary datasets, high-performance compute, and Lila's research infrastructure

Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation.

 
Application Requirement:
Please submit your resume alongside a research proposal (up to 3 pages, unlimited references) outlining the project you would plan to pursue during your residency at Lila Sciences. Please submit your research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials (e.g., recommendation letters, publications, research artifacts) may also be included. 

Your Impact at Lila

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila's world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and experienced mentors, you'll pursue ambitious research projects with both academic and real-world impact. Publishing is encouraged but not required - what matters most is pushing the frontier of scientific discovery.

What You'll Be Building

  • Design and execute independent research projects in AI for materials science
  • Collaborate with Lila scientists and engineers on cutting-edge, open-science initiatives
  • Explore domains such as ML-accelerated simulations, Bayesian methods, representation learning, generative AI, agentic science, and ML-driven automation
  • Contribute to collaborative team research and co-develop novel approaches to scientific discovery
  • Share findings internally and externally; publications are welcome but not mandatory

What You'll Need to Succeed

  • Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelor's, Master's, or PhD)
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch)
  • Experience working with large-scale datasets or simulations
  • Familiarity with modern AI/ML architectures and training techniques
  • Strong research background, demonstrated through publications, thesis work, or open-source projects

Bonus Points For

  • Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)
  • Familiarity with Bayesian optimization, active learning, or generative models
  • Experience in reinforcement learning or agent-based approaches to scientific reasoning
  • Open-source contributions or collaborative research experience
  • Strong communication and writing skills, especially for conveying complex scientific ideas